LONDON.- Researchers at Queen Mary University of London, in the United Kingdom, managed to develop a new predictive analysis that allows dementia to be detected nine years before an official diagnosis is made.
According to the report published in the magazine Naturethe novel procedure performed using MRI analysis has a precision of over 80% and greater accuracy than memory tests or brain shrinkage measurements currently used to diagnose dementia.
Analysis development
The team of scientists, led by professor and neurologist Charles Marshall, developed the test by analyzing functional magnetic resonance imaging (fMRI) scans to detect changes in the brain’s default mode network (DMN).
They explained that the DMN connects regions of the brain to perform specific cognitive functions and is the first neural network affected by Alzheimer’s disease.
To estimate the effective connectivity between ten brain regions that make up the default mode network, the researchers analyzed fMRI images of more than 1,100 volunteers from the UK Biobank, a large-scale biomedical and research database that contains genetic and health information on half a million British participants.
They assigned each patient a dementia probability value based on the extent to which their effective connectivity pattern matched a pattern indicative of dementia or a pattern similar to the control.
The experts also examined whether the changes in DMN could be caused by known risk factors for dementia.
The findings
After comparing the medical data of each patient, they found that the model could predict with a margin of error of two years the exact time it would take for the diagnosis.
The analysis also showed that genetic risk for Alzheimer’s disease was closely related to connectivity changes in the DMN, supporting the idea that these changes are specific to Alzheimer’s disease.
Furthermore, they found that social isolation is likely to increase the risk of dementia through its effect on connectivity in the DMN.
On the other hand, the specialists evaluated whether the changes in the DMN could be due to known risk factors for this disease such as genetics or habits such as smoking, diet, lack of sport or being overweight. The results showed that genetic risk for Alzheimer’s disease, the most common cause of dementia, was strongly associated with connectivity changes in the DMN.
Vital to develop new treatments
Charles Marshall, a member of the research team at the Center for Preventive Neurology at the Wolfson Institute of Health at Queen Mary, said that predicting who will suffer from dementia in the future will be vital to developing new treatments “that can prevent the irreversible loss of brain cells that causes symptoms of dementia
Marshall’s team hopes that the measure of brain function they have developed “will allow us to be much more precise about whether someone is actually going to get dementia, and over how long, so that we can identify whether they might benefit from future treatments.”
For his part, the lead author and doctor of the Academic Foundation Program at the Center for Preventive Neurology of the Wolfson Institute Samuel Ereira indicated that using these analysis techniques with large data sets, “people at high risk of dementia and also knowing what environmental risk factors pushed these people into a high-risk zone.”
He explained that fMRI is a non-invasive medical imaging tool, “which takes about 6 minutes to collect the necessary data in an MRI scanner, so it could be integrated into existing diagnostic pathways, especially where it is already used.” .
@Lydr05
Source: With information from Nature magazine and EuropaPress
